基于模糊调节的智能车路径跟随方法

Path Following Method of Intelligent Vehicles Based on Fuzzy Regulation

为提高智能车在不同速度下的路径跟随精度,提出一种基于模糊调节的智能车路径跟随方法。首先基于纯跟踪模型和运动学误差模型,分别设计纯跟踪(PP)控制器和线性二次型调节器(LQR);然后针对两种方法存在的跟随精度低和抗干扰能力弱等问题,提出一种以车速和曲率为输入、以PP方法控制量权重为输出的模糊调节策略;最后通过实车试验验证路径跟随方法的控制性能。结果表明,设计的控制器在不同速度下保持较高的跟随精度。

In order to improve the path following accuracy of intelligent vehicles at different speeds,a path following method of intelligent vehicle based on fuzzy regulation is proposed in this paper.Firstly,the pure pursuit(PP)controller and the linear quadratic regulator(LQR)are designed respectively based on the pure pursuit model and the kinematic error model.Then,aiming at the problems of low following accuracy and weak anti-interference ability of PP and LQR,a fuzzy regulation strategy with speed and curvature as input and PP method control quantity weight as output is proposed.Finally,the control performance of the path following method is verified by real vehicle test.The results show that the controller designed maintains high following accuracy at different speeds.